{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\Accepted-Final Articles 2014\Civil Wars\Webdata\CW2014.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 2 Feb 2015, 12:49:59
{txt}
{com}. 
. label variable maoist_event "Post-Accord Violence by Maoists"
{txt}
{com}. label variable bystate_2006 "Killed by State during Insurgency"
{txt}
{com}. label variable bymaoist_2006 "Killed by Maoists during Insurgency"
{txt}
{com}. label variable not_claimedevent "Post-Accord Violence not Claimed"
{txt}
{com}. label variable ethnic_event "Post-Accord Ethnic Group Violence"
{txt}
{com}. label variable landless_gap "% Landless Gap"
{txt}
{com}. label variable road_density "Road Density"
{txt}
{com}. label variable gap_institutional_credit "% Access to Institutional Credit Gap"
{txt}
{com}. label variable ln_pop2001 "Log Population 2001"
{txt}
{com}. label variable hdi_2001 "HDI 2001"
{txt}
{com}. label variable  abs_total "Absentee Population (1000)"
{txt}
{com}. label variable region_east "East Region"
{txt}
{com}. label variable region_west "West Region "
{txt}
{com}. label variable region_midwest "Midwest Region"
{txt}
{com}. label variable region_farwest "Far West Region"
{txt}
{com}. 
. 
. 
. set more off
{txt}
{com}. //TABLE 1 MODELS
. //Table 1/Model 1
. nbreg  maoist_event   bystate_2006 bymaoist_2006 not_claimedevent ethnic_event landless_gap  road_density  gap_institutional_credit ln_pop2001, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-225.83668}  
Iteration 1:{space 3}log pseudolikelihood = {res:-214.34091}  
Iteration 2:{space 3}log pseudolikelihood = {res:-214.23838}  
Iteration 3:{space 3}log pseudolikelihood = {res:-214.23835}  
Iteration 4:{space 3}log pseudolikelihood = {res:-214.23835}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-203.29752}  
Iteration 1:{space 3}log pseudolikelihood = {res:-202.65888}  
Iteration 2:{space 3}log pseudolikelihood = {res:-202.65887}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-191.61444}  
Iteration 1:{space 3}log pseudolikelihood = {res:-188.39835}  
Iteration 2:{space 3}log pseudolikelihood = {res:-187.26369}  
Iteration 3:{space 3}log pseudolikelihood = {res:-187.24314}  
Iteration 4:{space 3}log pseudolikelihood = {res:-187.24313}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}8{txt})    =  {res}    98.22
{txt}Log pseudolikelihood = {res}-187.24313                 {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}            maoist_event{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0024854{col 38}{space 2} .0008768{col 49}{space 1}    2.83{col 58}{space 3}0.005{col 66}{space 4} .0007669{col 79}{space 3} .0042039
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2}-.0033546{col 38}{space 2} .0025924{col 49}{space 1}   -1.29{col 58}{space 3}0.196{col 66}{space 4}-.0084356{col 79}{space 3} .0017264
{txt}{space 8}not_claimedevent {c |}{col 26}{res}{space 2}-.0013777{col 38}{space 2} .0756432{col 49}{space 1}   -0.02{col 58}{space 3}0.985{col 66}{space 4}-.1496356{col 79}{space 3} .1468802
{txt}{space 12}ethnic_event {c |}{col 26}{res}{space 2}-.0047739{col 38}{space 2}  .032183{col 49}{space 1}   -0.15{col 58}{space 3}0.882{col 66}{space 4}-.0678515{col 79}{space 3} .0583037
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .0281822{col 38}{space 2} .0074889{col 49}{space 1}    3.76{col 58}{space 3}0.000{col 66}{space 4} .0135043{col 79}{space 3} .0428602
{txt}{space 12}road_density {c |}{col 26}{res}{space 2}-1.756182{col 38}{space 2} .6166918{col 49}{space 1}   -2.85{col 58}{space 3}0.004{col 66}{space 4}-2.964876{col 79}{space 3}-.5474888
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0151717{col 38}{space 2}  .006226{col 49}{space 1}    2.44{col 58}{space 3}0.015{col 66}{space 4}  .002969{col 79}{space 3} .0273743
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2} .3560042{col 38}{space 2} .1923053{col 49}{space 1}    1.85{col 58}{space 3}0.064{col 66}{space 4}-.0209072{col 79}{space 3} .7329156
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-2.652934{col 38}{space 2} 2.338054{col 49}{space 1}   -1.13{col 58}{space 3}0.257{col 66}{space 4}-7.235435{col 79}{space 3} 1.929567
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                /lnalpha {c |}{col 26}{res}{space 2}-.9071418{col 38}{space 2} .3560035{col 66}{space 4}-1.604896{col 79}{space 3}-.2093877
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   alpha{col 26}{c |}{res}{space 2} .4036764{col 38}{space 2} .1437102{col 66}{space 4} .2009105{col 79}{space 3} .8110807
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. //Table 1/Model 2
. nbreg  maoist_event   bystate_2006 bymaoist_2006  landless_gap  road_density  gap_institutional_credit hdi_2001  abs_total ln_pop2001, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-225.56112}  
Iteration 1:{space 3}log pseudolikelihood = {res:-215.46856}  
Iteration 2:{space 3}log pseudolikelihood = {res:-215.40203}  
Iteration 3:{space 3}log pseudolikelihood = {res:-215.40202}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-203.29752}  
Iteration 1:{space 3}log pseudolikelihood = {res:-202.65888}  
Iteration 2:{space 3}log pseudolikelihood = {res:-202.65887}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-191.62684}  
Iteration 1:{space 3}log pseudolikelihood = {res:-188.39047}  
Iteration 2:{space 3}log pseudolikelihood = {res:-187.37958}  
Iteration 3:{space 3}log pseudolikelihood = {res:-187.36373}  
Iteration 4:{space 3}log pseudolikelihood = {res:-187.36373}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}8{txt})    =  {res}    97.69
{txt}Log pseudolikelihood = {res}-187.36373                 {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}            maoist_event{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}bystate_2006 {c |}{col 26}{res}{space 2}  .002498{col 38}{space 2} .0008664{col 49}{space 1}    2.88{col 58}{space 3}0.004{col 66}{space 4} .0007999{col 79}{space 3} .0041961
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2}-.0033828{col 38}{space 2} .0026202{col 49}{space 1}   -1.29{col 58}{space 3}0.197{col 66}{space 4}-.0085182{col 79}{space 3} .0017527
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .0283743{col 38}{space 2} .0067571{col 49}{space 1}    4.20{col 58}{space 3}0.000{col 66}{space 4} .0151305{col 79}{space 3}  .041618
{txt}{space 12}road_density {c |}{col 26}{res}{space 2}-1.674654{col 38}{space 2} .6337518{col 49}{space 1}   -2.64{col 58}{space 3}0.008{col 66}{space 4}-2.916785{col 79}{space 3} -.432523
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0160154{col 38}{space 2} .0068271{col 49}{space 1}    2.35{col 58}{space 3}0.019{col 66}{space 4} .0026345{col 79}{space 3} .0293963
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2} -.721137{col 38}{space 2} 1.750368{col 49}{space 1}   -0.41{col 58}{space 3}0.680{col 66}{space 4}-4.151796{col 79}{space 3} 2.709522
{txt}{space 15}abs_total {c |}{col 26}{res}{space 2}-1.74e-06{col 38}{space 2} 9.95e-06{col 49}{space 1}   -0.18{col 58}{space 3}0.861{col 66}{space 4}-.0000212{col 79}{space 3} .0000178
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2} .3433127{col 38}{space 2} .1799614{col 49}{space 1}    1.91{col 58}{space 3}0.056{col 66}{space 4}-.0094052{col 79}{space 3} .6960306
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-2.189735{col 38}{space 2} 2.323059{col 49}{space 1}   -0.94{col 58}{space 3}0.346{col 66}{space 4}-6.742846{col 79}{space 3} 2.363376
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                /lnalpha {c |}{col 26}{res}{space 2}-.8945537{col 38}{space 2}  .352173{col 66}{space 4}  -1.5848{col 79}{space 3}-.2043072
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   alpha{col 26}{c |}{res}{space 2}   .40879{col 38}{space 2} .1439648{col 66}{space 4} .2049888{col 79}{space 3} .8152119
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. //Table 1//Model 3
. nbreg  maoist_event   bystate_2006 bymaoist_2006  landless_gap  road_density  gap_institutional_credit ln_pop2001 region_east region_west region_midwest region_farwest, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-216.15217}  
Iteration 1:{space 3}log pseudolikelihood = {res:-207.96997}  
Iteration 2:{space 3}log pseudolikelihood = {res:-207.92819}  
Iteration 3:{space 3}log pseudolikelihood = {res:-207.92818}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-203.29752}  
Iteration 1:{space 3}log pseudolikelihood = {res:-202.65888}  
Iteration 2:{space 3}log pseudolikelihood = {res:-202.65887}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-190.40677}  
Iteration 1:{space 3}log pseudolikelihood = {res:-187.48632}  
Iteration 2:{space 3}log pseudolikelihood = {res:-184.75081}  
Iteration 3:{space 3}log pseudolikelihood = {res:-184.64597}  
Iteration 4:{space 3}log pseudolikelihood = {res: -184.6457}  
Iteration 5:{space 3}log pseudolikelihood = {res: -184.6457}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}10{txt})   =  {res}   159.33
{txt}Log pseudolikelihood = {res}-184.6457                  {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}            maoist_event{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0028889{col 38}{space 2} .0008544{col 49}{space 1}    3.38{col 58}{space 3}0.001{col 66}{space 4} .0012142{col 79}{space 3} .0045636
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2}-.0049404{col 38}{space 2}  .002748{col 49}{space 1}   -1.80{col 58}{space 3}0.072{col 66}{space 4}-.0103263{col 79}{space 3} .0004455
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .0289529{col 38}{space 2} .0074453{col 49}{space 1}    3.89{col 58}{space 3}0.000{col 66}{space 4} .0143605{col 79}{space 3} .0435454
{txt}{space 12}road_density {c |}{col 26}{res}{space 2}-1.949496{col 38}{space 2} .7059862{col 49}{space 1}   -2.76{col 58}{space 3}0.006{col 66}{space 4}-3.333203{col 79}{space 3}-.5657881
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0182532{col 38}{space 2} .0050638{col 49}{space 1}    3.60{col 58}{space 3}0.000{col 66}{space 4} .0083283{col 79}{space 3} .0281781
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2} .3680103{col 38}{space 2} .1854996{col 49}{space 1}    1.98{col 58}{space 3}0.047{col 66}{space 4} .0044378{col 79}{space 3} .7315829
{txt}{space 13}region_east {c |}{col 26}{res}{space 2}-.3229067{col 38}{space 2} .3412465{col 49}{space 1}   -0.95{col 58}{space 3}0.344{col 66}{space 4}-.9917375{col 79}{space 3} .3459241
{txt}{space 13}region_west {c |}{col 26}{res}{space 2}-.2099939{col 38}{space 2} .3514141{col 49}{space 1}   -0.60{col 58}{space 3}0.550{col 66}{space 4}-.8987528{col 79}{space 3}  .478765
{txt}{space 10}region_midwest {c |}{col 26}{res}{space 2}-.0901797{col 38}{space 2} .3581067{col 49}{space 1}   -0.25{col 58}{space 3}0.801{col 66}{space 4} -.792056{col 79}{space 3} .6116965
{txt}{space 10}region_farwest {c |}{col 26}{res}{space 2}-.8389665{col 38}{space 2} .4844874{col 49}{space 1}   -1.73{col 58}{space 3}0.083{col 66}{space 4}-1.788544{col 79}{space 3} .1106114
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} -2.51673{col 38}{space 2} 2.260888{col 49}{space 1}   -1.11{col 58}{space 3}0.266{col 66}{space 4} -6.94799{col 79}{space 3} 1.914529
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                /lnalpha {c |}{col 26}{res}{space 2}-1.016326{col 38}{space 2} .3773313{col 66}{space 4}-1.755881{col 79}{space 3}  -.27677
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   alpha{col 26}{c |}{res}{space 2} .3619223{col 38}{space 2} .1365646{col 66}{space 4} .1727549{col 79}{space 3} .7582289
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. //Table 1//Model 4
. nbreg  maoist_event   bystate_2006 bymaoist_2006  landless_gap  road_density  gap_institutional_credit hdi_2001  ln_pop2001, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-225.42896}  
Iteration 1:{space 3}log pseudolikelihood = {res:-215.46662}  
Iteration 2:{space 3}log pseudolikelihood = {res:-215.40296}  
Iteration 3:{space 3}log pseudolikelihood = {res:-215.40295}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-203.29752}  
Iteration 1:{space 3}log pseudolikelihood = {res:-202.65888}  
Iteration 2:{space 3}log pseudolikelihood = {res:-202.65887}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-191.62819}  
Iteration 1:{space 3}log pseudolikelihood = {res:-188.37826}  
Iteration 2:{space 3}log pseudolikelihood = {res:-187.38978}  
Iteration 3:{space 3}log pseudolikelihood = {res:-187.37456}  
Iteration 4:{space 3}log pseudolikelihood = {res:-187.37456}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}7{txt})    =  {res}    93.12
{txt}Log pseudolikelihood = {res}-187.37456                 {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}            maoist_event{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0024934{col 38}{space 2}  .000871{col 49}{space 1}    2.86{col 58}{space 3}0.004{col 66}{space 4} .0007861{col 79}{space 3} .0042006
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2}-.0033544{col 38}{space 2}  .002616{col 49}{space 1}   -1.28{col 58}{space 3}0.200{col 66}{space 4}-.0084817{col 79}{space 3} .0017729
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .0282663{col 38}{space 2} .0067987{col 49}{space 1}    4.16{col 58}{space 3}0.000{col 66}{space 4}  .014941{col 79}{space 3} .0415916
{txt}{space 12}road_density {c |}{col 26}{res}{space 2}-1.657154{col 38}{space 2} .6339486{col 49}{space 1}   -2.61{col 58}{space 3}0.009{col 66}{space 4}-2.899671{col 79}{space 3}-.4146377
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0159619{col 38}{space 2} .0068632{col 49}{space 1}    2.33{col 58}{space 3}0.020{col 66}{space 4} .0025103{col 79}{space 3} .0294135
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2}-.7915157{col 38}{space 2} 1.740097{col 49}{space 1}   -0.45{col 58}{space 3}0.649{col 66}{space 4}-4.202044{col 79}{space 3} 2.619012
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2} .3353148{col 38}{space 2}  .173756{col 49}{space 1}    1.93{col 58}{space 3}0.054{col 66}{space 4}-.0052407{col 79}{space 3} .6758703
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} -2.08155{col 38}{space 2} 2.264698{col 49}{space 1}   -0.92{col 58}{space 3}0.358{col 66}{space 4}-6.520277{col 79}{space 3} 2.357178
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                /lnalpha {c |}{col 26}{res}{space 2}-.8946664{col 38}{space 2} .3528502{col 66}{space 4} -1.58624{col 79}{space 3}-.2030927
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   alpha{col 26}{c |}{res}{space 2} .4087439{col 38}{space 2} .1442254{col 66}{space 4} .2046938{col 79}{space 3} .8162025
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //TABLE 2 MODELS
. //Table 2/FPTP votes model 1 & 2
. reg maoistvote2008_1000 ncvote2008_1000 cpnumlvote2008_1000 no_candidates_2008 maoist_event  bystate_2006 bymaoist_2006  not_claimedevent ethnic_event road_density landless_gap gap_institutional_credit ln_pop2001 hdi_2001, r

{txt}Linear regression                                      Number of obs ={res}      75
                                                       {txt}F( 13,    61) ={res}   49.73
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.6983
                                                       {txt}Root MSE      = {res}  16.44

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}     maoistvote2008_1000{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      t{col 58}   P>|t|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ncvote2008_1000 {c |}{col 26}{res}{space 2}  .360641{col 38}{space 2} .2677404{col 49}{space 1}    1.35{col 58}{space 3}0.183{col 66}{space 4} -.174739{col 79}{space 3} .8960211
{txt}{space 5}cpnumlvote2008_1000 {c |}{col 26}{res}{space 2} .0533562{col 38}{space 2} .3393794{col 49}{space 1}    0.16{col 58}{space 3}0.876{col 66}{space 4} -.625275{col 79}{space 3} .7319873
{txt}{space 6}no_candidates_2008 {c |}{col 26}{res}{space 2}-.0834382{col 38}{space 2} .1001684{col 49}{space 1}   -0.83{col 58}{space 3}0.408{col 66}{space 4}-.2837372{col 79}{space 3} .1168608
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} 1.097658{col 38}{space 2} .5154023{col 49}{space 1}    2.13{col 58}{space 3}0.037{col 66}{space 4} .0670477{col 79}{space 3} 2.128269
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0056762{col 38}{space 2} .0258861{col 49}{space 1}    0.22{col 58}{space 3}0.827{col 66}{space 4}-.0460863{col 79}{space 3} .0574386
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2} .1837955{col 38}{space 2}  .059262{col 49}{space 1}    3.10{col 58}{space 3}0.003{col 66}{space 4} .0652938{col 79}{space 3} .3022971
{txt}{space 8}not_claimedevent {c |}{col 26}{res}{space 2} .4584908{col 38}{space 2} 1.401715{col 49}{space 1}    0.33{col 58}{space 3}0.745{col 66}{space 4}-2.344412{col 79}{space 3} 3.261393
{txt}{space 12}ethnic_event {c |}{col 26}{res}{space 2}-.5251314{col 38}{space 2} .6812777{col 49}{space 1}   -0.77{col 58}{space 3}0.444{col 66}{space 4} -1.88743{col 79}{space 3} .8371676
{txt}{space 12}road_density {c |}{col 26}{res}{space 2}-2.837172{col 38}{space 2} 8.029939{col 49}{space 1}   -0.35{col 58}{space 3}0.725{col 66}{space 4}-18.89403{col 79}{space 3} 13.21968
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .1157352{col 38}{space 2} .2082737{col 49}{space 1}    0.56{col 58}{space 3}0.580{col 66}{space 4}-.3007339{col 79}{space 3} .5322043
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0287224{col 38}{space 2} .1549705{col 49}{space 1}    0.19{col 58}{space 3}0.854{col 66}{space 4}-.2811602{col 79}{space 3} .3386051
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2} 8.832751{col 38}{space 2} 5.371547{col 49}{space 1}    1.64{col 58}{space 3}0.105{col 66}{space 4} -1.90832{col 79}{space 3} 19.57382
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2} 26.29946{col 38}{space 2}  31.1089{col 49}{space 1}    0.85{col 58}{space 3}0.401{col 66}{space 4}-35.90664{col 79}{space 3} 88.50556
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} -104.123{col 38}{space 2} 59.87794{col 49}{space 1}   -1.74{col 58}{space 3}0.087{col 66}{space 4}-223.8564{col 79}{space 3} 15.61031
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg maoistvote2008_1000 ncvote2008_1000 cpnumlvote2008_1000 no_candidates_2008 maoist_event  bystate_2006 bymaoist_2006  landless_gap gap_institutional_credit ln_pop2001 hdi_2001, r

{txt}Linear regression                                      Number of obs ={res}      75
                                                       {txt}F( 10,    64) ={res}   63.59
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.6898
                                                       {txt}Root MSE      = {res} 16.275

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}     maoistvote2008_1000{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      t{col 58}   P>|t|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ncvote2008_1000 {c |}{col 26}{res}{space 2} .4338508{col 38}{space 2} .2689211{col 49}{space 1}    1.61{col 58}{space 3}0.112{col 66}{space 4}-.1033809{col 79}{space 3} .9710826
{txt}{space 5}cpnumlvote2008_1000 {c |}{col 26}{res}{space 2} .0873008{col 38}{space 2} .3185774{col 49}{space 1}    0.27{col 58}{space 3}0.785{col 66}{space 4}-.5491308{col 79}{space 3} .7237323
{txt}{space 6}no_candidates_2008 {c |}{col 26}{res}{space 2}-.1788264{col 38}{space 2} .0644508{col 49}{space 1}   -2.77{col 58}{space 3}0.007{col 66}{space 4}-.3075817{col 79}{space 3} -.050071
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} 1.172596{col 38}{space 2} .4719301{col 49}{space 1}    2.48{col 58}{space 3}0.016{col 66}{space 4} .2298076{col 79}{space 3} 2.115385
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0046184{col 38}{space 2} .0250447{col 49}{space 1}    0.18{col 58}{space 3}0.854{col 66}{space 4}-.0454141{col 79}{space 3} .0546508
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2} .2006931{col 38}{space 2} .0609985{col 49}{space 1}    3.29{col 58}{space 3}0.002{col 66}{space 4} .0788346{col 79}{space 3} .3225516
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .1848661{col 38}{space 2} .1583799{col 49}{space 1}    1.17{col 58}{space 3}0.247{col 66}{space 4}-.1315341{col 79}{space 3} .5012663
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0133487{col 38}{space 2} .1503857{col 49}{space 1}    0.09{col 58}{space 3}0.930{col 66}{space 4}-.2870812{col 79}{space 3} .3137786
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2}   7.8126{col 38}{space 2} 4.483505{col 49}{space 1}    1.74{col 58}{space 3}0.086{col 66}{space 4}-1.144232{col 79}{space 3} 16.76943
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2} 27.88286{col 38}{space 2} 29.10202{col 49}{space 1}    0.96{col 58}{space 3}0.342{col 66}{space 4}-30.25511{col 79}{space 3} 86.02084
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-93.56656{col 38}{space 2} 49.92068{col 49}{space 1}   -1.87{col 58}{space 3}0.065{col 66}{space 4}-193.2946{col 79}{space 3} 6.161471
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. //Table 2/PR votes model 3&4 
. reg prv_maoist2008_1000 prv_nc2008_1000 prv_uml2008_1000 maoist_event  bystate_2006 bymaoist_2006  not_claimedevent ethnic_event road_density landless_gap gap_institutional_credit ln_pop2001 hdi_2001, r

{txt}Linear regression                                      Number of obs ={res}      75
                                                       {txt}F( 12,    62) ={res}   15.04
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.5757
                                                       {txt}Root MSE      = {res} 19.697

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}     prv_maoist2008_1000{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      t{col 58}   P>|t|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}prv_nc2008_1000 {c |}{col 26}{res}{space 2} 1.024941{col 38}{space 2} .1256405{col 49}{space 1}    8.16{col 58}{space 3}0.000{col 66}{space 4}  .773789{col 79}{space 3} 1.276093
{txt}{space 8}prv_uml2008_1000 {c |}{col 26}{res}{space 2}-.0382949{col 38}{space 2} .0726392{col 49}{space 1}   -0.53{col 58}{space 3}0.600{col 66}{space 4}-.1834986{col 79}{space 3} .1069088
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} .9899354{col 38}{space 2} .4553919{col 49}{space 1}    2.17{col 58}{space 3}0.034{col 66}{space 4} .0796199{col 79}{space 3} 1.900251
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0244669{col 38}{space 2} .0226237{col 49}{space 1}    1.08{col 58}{space 3}0.284{col 66}{space 4}-.0207572{col 79}{space 3}  .069691
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2}  .075514{col 38}{space 2} .0604631{col 49}{space 1}    1.25{col 58}{space 3}0.216{col 66}{space 4}  -.04535{col 79}{space 3} .1963781
{txt}{space 8}not_claimedevent {c |}{col 26}{res}{space 2}-1.936469{col 38}{space 2} 2.419492{col 49}{space 1}   -0.80{col 58}{space 3}0.427{col 66}{space 4}-6.772966{col 79}{space 3} 2.900027
{txt}{space 12}ethnic_event {c |}{col 26}{res}{space 2} .8821729{col 38}{space 2} .9601776{col 49}{space 1}    0.92{col 58}{space 3}0.362{col 66}{space 4}-1.037195{col 79}{space 3} 2.801541
{txt}{space 12}road_density {c |}{col 26}{res}{space 2} 13.54718{col 38}{space 2} 15.66825{col 49}{space 1}    0.86{col 58}{space 3}0.391{col 66}{space 4} -17.7732{col 79}{space 3} 44.86756
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2}  .072432{col 38}{space 2} .1981083{col 49}{space 1}    0.37{col 58}{space 3}0.716{col 66}{space 4}-.3235809{col 79}{space 3} .4684449
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0173137{col 38}{space 2} .1339922{col 49}{space 1}    0.13{col 58}{space 3}0.898{col 66}{space 4}-.2505329{col 79}{space 3} .2851603
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2}-6.799181{col 38}{space 2}  2.84151{col 49}{space 1}   -2.39{col 58}{space 3}0.020{col 66}{space 4}-12.47928{col 79}{space 3}-1.119083
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2}-24.72677{col 38}{space 2} 51.54838{col 49}{space 1}   -0.48{col 58}{space 3}0.633{col 66}{space 4}-127.7705{col 79}{space 3} 78.31697
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} 92.52287{col 38}{space 2} 40.34952{col 49}{space 1}    2.29{col 58}{space 3}0.025{col 66}{space 4} 11.86534{col 79}{space 3} 173.1804
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg prv_maoist2008_1000 prv_nc2008_1000 prv_uml2008_1000 maoist_event  bystate_2006 bymaoist_2006  landless_gap gap_institutional_credit ln_pop2001 hdi_2001, r

{txt}Linear regression                                      Number of obs ={res}      75
                                                       {txt}F(  9,    65) ={res}   14.42
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.5620
                                                       {txt}Root MSE      = {res} 19.544

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}     prv_maoist2008_1000{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      t{col 58}   P>|t|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}prv_nc2008_1000 {c |}{col 26}{res}{space 2} 1.045363{col 38}{space 2} .1273384{col 49}{space 1}    8.21{col 58}{space 3}0.000{col 66}{space 4} .7910511{col 79}{space 3} 1.299676
{txt}{space 8}prv_uml2008_1000 {c |}{col 26}{res}{space 2}-.0613091{col 38}{space 2} .0657735{col 49}{space 1}   -0.93{col 58}{space 3}0.355{col 66}{space 4}-.1926679{col 79}{space 3} .0700498
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} .8545233{col 38}{space 2} .4299176{col 49}{space 1}    1.99{col 58}{space 3}0.051{col 66}{space 4}-.0040815{col 79}{space 3} 1.713128
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0174519{col 38}{space 2} .0220708{col 49}{space 1}    0.79{col 58}{space 3}0.432{col 66}{space 4}-.0266266{col 79}{space 3} .0615304
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2} .0653145{col 38}{space 2} .0635997{col 49}{space 1}    1.03{col 58}{space 3}0.308{col 66}{space 4} -.061703{col 79}{space 3} .1923319
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .1667823{col 38}{space 2} .1091076{col 49}{space 1}    1.53{col 58}{space 3}0.131{col 66}{space 4}-.0511205{col 79}{space 3} .3846852
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0014731{col 38}{space 2} .1320876{col 49}{space 1}    0.01{col 58}{space 3}0.991{col 66}{space 4} -.262324{col 79}{space 3} .2652702
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2}-5.748483{col 38}{space 2} 2.717006{col 49}{space 1}   -2.12{col 58}{space 3}0.038{col 66}{space 4}-11.17472{col 79}{space 3}-.3222469
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2}-21.26701{col 38}{space 2} 50.29809{col 49}{space 1}   -0.42{col 58}{space 3}0.674{col 66}{space 4}-121.7192{col 79}{space 3} 79.18521
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} 82.24554{col 38}{space 2} 40.70458{col 49}{space 1}    2.02{col 58}{space 3}0.047{col 66}{space 4} .9528694{col 79}{space 3} 163.5382
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. //TABLE 3 - EFFECT ON FPTP SEATS model 1, 2, & 3
. 
. nbreg seat_cpnm_2008 seat_nc2008 seat_cpnuml_2008 landless_gap no_candidates_2008 maoist_event   not_claimedevent ethnic_event   bystate_2006  bymaoist_2006 ln_pop2001 hdi_2001 gap_institutional_credit, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-93.482714}  
Iteration 1:{space 3}log pseudolikelihood = {res:-93.440336}  
Iteration 2:{space 3}log pseudolikelihood = {res:-93.440252}  
Iteration 3:{space 3}log pseudolikelihood = {res:-93.440252}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -129.9243}  
Iteration 1:{space 3}log pseudolikelihood = {res:-120.46267}  
Iteration 2:{space 3}log pseudolikelihood = {res:-120.43803}  
Iteration 3:{space 3}log pseudolikelihood = {res:-120.43678}  
Iteration 4:{space 3}log pseudolikelihood = {res:-120.43678}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-99.588123}  
Iteration 1:{space 3}log pseudolikelihood = {res:-94.157872}  
Iteration 2:{space 3}log pseudolikelihood = {res:-93.605992}  
Iteration 3:{space 3}log pseudolikelihood = {res:-93.472168}  
Iteration 4:{space 3}log pseudolikelihood = {res: -93.44746}  
Iteration 5:{space 3}log pseudolikelihood = {res:-93.441924}  
Iteration 6:{space 3}log pseudolikelihood = {res:-93.440618}  
Iteration 7:{space 3}log pseudolikelihood = {res:-93.440328}  
Iteration 8:{space 3}log pseudolikelihood = {res:-93.440264}  
Iteration 9:{space 3}log pseudolikelihood = {res:-93.440252}  
Iteration 10:{space 2}log pseudolikelihood = {res:-93.440252}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}12{txt})   =  {res}   330.34
{txt}Log pseudolikelihood = {res}-93.440252                 {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}          seat_cpnm_2008{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}seat_nc2008 {c |}{col 26}{res}{space 2}-.4275442{col 38}{space 2} .1195831{col 49}{space 1}   -3.58{col 58}{space 3}0.000{col 66}{space 4}-.6619228{col 79}{space 3}-.1931657
{txt}{space 8}seat_cpnuml_2008 {c |}{col 26}{res}{space 2}-.5838637{col 38}{space 2} .1157322{col 49}{space 1}   -5.04{col 58}{space 3}0.000{col 66}{space 4}-.8106947{col 79}{space 3}-.3570328
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .0019608{col 38}{space 2} .0064027{col 49}{space 1}    0.31{col 58}{space 3}0.759{col 66}{space 4}-.0105882{col 79}{space 3} .0145099
{txt}{space 6}no_candidates_2008 {c |}{col 26}{res}{space 2} .0029518{col 38}{space 2} .0048706{col 49}{space 1}    0.61{col 58}{space 3}0.544{col 66}{space 4}-.0065944{col 79}{space 3} .0124981
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} .0263584{col 38}{space 2} .0126982{col 49}{space 1}    2.08{col 58}{space 3}0.038{col 66}{space 4} .0014704{col 79}{space 3} .0512464
{txt}{space 8}not_claimedevent {c |}{col 26}{res}{space 2}   .14056{col 38}{space 2} .0836245{col 49}{space 1}    1.68{col 58}{space 3}0.093{col 66}{space 4} -.023341{col 79}{space 3} .3044611
{txt}{space 12}ethnic_event {c |}{col 26}{res}{space 2}-.1016552{col 38}{space 2} .0441078{col 49}{space 1}   -2.30{col 58}{space 3}0.021{col 66}{space 4} -.188105{col 79}{space 3}-.0152054
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2}-.0007445{col 38}{space 2} .0006407{col 49}{space 1}   -1.16{col 58}{space 3}0.245{col 66}{space 4}-.0020003{col 79}{space 3} .0005112
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2} .0018903{col 38}{space 2} .0016553{col 49}{space 1}    1.14{col 58}{space 3}0.253{col 66}{space 4}-.0013541{col 79}{space 3} .0051346
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2} .5438492{col 38}{space 2} .2084957{col 49}{space 1}    2.61{col 58}{space 3}0.009{col 66}{space 4} .1352052{col 79}{space 3} .9524932
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2} .4276686{col 38}{space 2} 1.287498{col 49}{space 1}    0.33{col 58}{space 3}0.740{col 66}{space 4}-2.095782{col 79}{space 3} 2.951119
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2}-.0017014{col 38}{space 2}  .003985{col 49}{space 1}   -0.43{col 58}{space 3}0.669{col 66}{space 4}-.0095119{col 79}{space 3}  .006109
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-6.453059{col 38}{space 2} 2.281513{col 49}{space 1}   -2.83{col 58}{space 3}0.005{col 66}{space 4}-10.92474{col 79}{space 3}-1.981376
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                /lnalpha {c |}{col 26}{res}{space 2}-21.23982{col 38}{space 2}        .{col 66}{space 4}        .{col 79}{space 3}        .
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   alpha{col 26}{c |}{res}{space 2} 5.97e-10{col 38}{space 2}        .{col 66}{space 4}        .{col 79}{space 3}        .
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. nbreg seat_cpnm_2008 seat_nc2008 seat_cpnuml_2008 road_density maoist_event   ethnic_event   bystate_2006  bymaoist_2006 ln_pop2001 hdi_2001, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-95.696074}  
Iteration 1:{space 3}log pseudolikelihood = {res: -95.68644}  
Iteration 2:{space 3}log pseudolikelihood = {res:-95.686439}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -129.9243}  
Iteration 1:{space 3}log pseudolikelihood = {res:-120.46267}  
Iteration 2:{space 3}log pseudolikelihood = {res:-120.43803}  
Iteration 3:{space 3}log pseudolikelihood = {res:-120.43678}  
Iteration 4:{space 3}log pseudolikelihood = {res:-120.43678}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-101.30665}  
Iteration 1:{space 3}log pseudolikelihood = {res:-96.333034}  
Iteration 2:{space 3}log pseudolikelihood = {res:-95.842129}  
Iteration 3:{space 3}log pseudolikelihood = {res:-95.721337}  
Iteration 4:{space 3}log pseudolikelihood = {res:-95.694766}  
Iteration 5:{space 3}log pseudolikelihood = {res:-95.688145}  
Iteration 6:{space 3}log pseudolikelihood = {res:-95.686811}  
Iteration 7:{space 3}log pseudolikelihood = {res:-95.686524}  
Iteration 8:{space 3}log pseudolikelihood = {res:-95.686459}  
Iteration 9:{space 3}log pseudolikelihood = {res:-95.686443}  
Iteration 10:{space 2}log pseudolikelihood = {res:-95.686439}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}9{txt})    =  {res}   116.81
{txt}Log pseudolikelihood = {res}-95.686439                 {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  seat_cpnm_2008{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}seat_nc2008 {c |}{col 18}{res}{space 2}-.2299514{col 30}{space 2} .0980717{col 41}{space 1}   -2.34{col 50}{space 3}0.019{col 58}{space 4}-.4221683{col 71}{space 3}-.0377344
{txt}seat_cpnuml_2008 {c |}{col 18}{res}{space 2}-.5948972{col 30}{space 2} .1209234{col 41}{space 1}   -4.92{col 50}{space 3}0.000{col 58}{space 4}-.8319027{col 71}{space 3}-.3578918
{txt}{space 4}road_density {c |}{col 18}{res}{space 2}-.0943229{col 30}{space 2} .3589099{col 41}{space 1}   -0.26{col 50}{space 3}0.793{col 58}{space 4}-.7977733{col 71}{space 3} .6091275
{txt}{space 4}maoist_event {c |}{col 18}{res}{space 2} .0325293{col 30}{space 2} .0120868{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0088397{col 71}{space 3}  .056219
{txt}{space 4}ethnic_event {c |}{col 18}{res}{space 2}-.0329699{col 30}{space 2} .0091883{col 41}{space 1}   -3.59{col 50}{space 3}0.000{col 58}{space 4}-.0509785{col 71}{space 3}-.0149612
{txt}{space 4}bystate_2006 {c |}{col 18}{res}{space 2}-.0002673{col 30}{space 2} .0006003{col 41}{space 1}   -0.45{col 50}{space 3}0.656{col 58}{space 4}-.0014439{col 71}{space 3} .0009093
{txt}{space 3}bymaoist_2006 {c |}{col 18}{res}{space 2} .0022309{col 30}{space 2} .0015666{col 41}{space 1}    1.42{col 50}{space 3}0.154{col 58}{space 4}-.0008396{col 71}{space 3} .0053015
{txt}{space 6}ln_pop2001 {c |}{col 18}{res}{space 2} .6603768{col 30}{space 2} .1925877{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} .2829118{col 71}{space 3} 1.037842
{txt}{space 8}hdi_2001 {c |}{col 18}{res}{space 2} 1.629083{col 30}{space 2} 1.248234{col 41}{space 1}    1.31{col 50}{space 3}0.192{col 58}{space 4}  -.81741{col 71}{space 3} 4.075576
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-8.425289{col 30}{space 2} 2.105937{col 41}{space 1}   -4.00{col 50}{space 3}0.000{col 58}{space 4}-12.55285{col 71}{space 3}-4.297728
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /lnalpha {c |}{col 18}{res}{space 2}-17.10573{col 30}{space 2} .0946562{col 58}{space 4}-17.29125{col 71}{space 3} -16.9202
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           alpha{col 18}{c |}{res}{space 2} 3.72e-08{col 30}{space 2} 3.53e-09{col 58}{space 4} 3.09e-08{col 71}{space 3} 4.48e-08
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. nbreg seat_cpnm_2008 seat_nc2008 seat_cpnuml_2008 road_density maoist_event   bystate_2006  bymaoist_2006 ln_pop2001, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-101.67337}  
Iteration 1:{space 3}log pseudolikelihood = {res:-101.67102}  
Iteration 2:{space 3}log pseudolikelihood = {res:-101.67102}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -129.9243}  
Iteration 1:{space 3}log pseudolikelihood = {res:-120.46267}  
Iteration 2:{space 3}log pseudolikelihood = {res:-120.43803}  
Iteration 3:{space 3}log pseudolikelihood = {res:-120.43678}  
Iteration 4:{space 3}log pseudolikelihood = {res:-120.43678}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-104.87755}  
Iteration 1:{space 3}log pseudolikelihood = {res:-102.16835}  
Iteration 2:{space 3}log pseudolikelihood = {res:-101.78049}  
Iteration 3:{space 3}log pseudolikelihood = {res:-101.69379}  
Iteration 4:{space 3}log pseudolikelihood = {res:-101.67624}  
Iteration 5:{space 3}log pseudolikelihood = {res:-101.67225}  
Iteration 6:{space 3}log pseudolikelihood = {res:-101.67127}  
Iteration 7:{space 3}log pseudolikelihood = {res:-101.67107}  
Iteration 8:{space 3}log pseudolikelihood = {res:-101.67103}  
Iteration 9:{space 3}log pseudolikelihood = {res:-101.67102}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}7{txt})    =  {res}    90.76
{txt}Log pseudolikelihood = {res}-101.67102                 {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  seat_cpnm_2008{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}seat_nc2008 {c |}{col 18}{res}{space 2}-.2159198{col 30}{space 2} .1017982{col 41}{space 1}   -2.12{col 50}{space 3}0.034{col 58}{space 4}-.4154406{col 71}{space 3}-.0163989
{txt}seat_cpnuml_2008 {c |}{col 18}{res}{space 2}-.4753914{col 30}{space 2} .1369399{col 41}{space 1}   -3.47{col 50}{space 3}0.001{col 58}{space 4}-.7437887{col 71}{space 3}-.2069942
{txt}{space 4}road_density {c |}{col 18}{res}{space 2} .2383199{col 30}{space 2} .3511324{col 41}{space 1}    0.68{col 50}{space 3}0.497{col 58}{space 4}-.4498869{col 71}{space 3} .9265268
{txt}{space 4}maoist_event {c |}{col 18}{res}{space 2} .0389933{col 30}{space 2} .0136589{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0122223{col 71}{space 3} .0657643
{txt}{space 4}bystate_2006 {c |}{col 18}{res}{space 2}-.0004199{col 30}{space 2} .0006843{col 41}{space 1}   -0.61{col 50}{space 3}0.539{col 58}{space 4}-.0017611{col 71}{space 3} .0009213
{txt}{space 3}bymaoist_2006 {c |}{col 18}{res}{space 2} .0037557{col 30}{space 2}  .001674{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0004748{col 71}{space 3} .0070366
{txt}{space 6}ln_pop2001 {c |}{col 18}{res}{space 2} .3829613{col 30}{space 2} .1488593{col 41}{space 1}    2.57{col 50}{space 3}0.010{col 58}{space 4} .0912025{col 71}{space 3} .6747201
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-4.565937{col 30}{space 2} 1.740187{col 41}{space 1}   -2.62{col 50}{space 3}0.009{col 58}{space 4} -7.97664{col 71}{space 3}-1.155234
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /lnalpha {c |}{col 18}{res}{space 2}-16.43882{col 30}{space 2} .7932794{col 58}{space 4}-17.99362{col 71}{space 3}-14.88402
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           alpha{col 18}{c |}{res}{space 2} 7.26e-08{col 30}{space 2} 5.76e-08{col 58}{space 4} 1.53e-08{col 71}{space 3} 3.44e-07
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. ////////////////////end///////////
> 
. //Table 1/Model 2
. nbreg  maoist_event   bystate_2006 bymaoist_2006 landless_gap  road_density  gap_institutional_credit ln_pop2001 hdi_2001

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-225.42896}  
Iteration 1:{space 3}log likelihood = {res:-215.46662}  
Iteration 2:{space 3}log likelihood = {res:-215.40296}  
Iteration 3:{space 3}log likelihood = {res:-215.40295}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-203.29752}  
Iteration 1:{space 3}log likelihood = {res:-202.65888}  
Iteration 2:{space 3}log likelihood = {res:-202.65887}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-191.62819}  
Iteration 1:{space 3}log likelihood = {res:-188.37826}  
Iteration 2:{space 3}log likelihood = {res:-187.38978}  
Iteration 3:{space 3}log likelihood = {res:-187.37456}  
Iteration 4:{space 3}log likelihood = {res:-187.37456}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
                                                  {txt}LR chi2({res}7{txt})      =  {res}    30.57
{txt}Dispersion     = {res}mean                             {txt}Prob > chi2     =  {res}   0.0001
{txt}Log likelihood = {res}-187.37456                       {txt}Pseudo R2       =  {res}   0.0754

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            maoist_event{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0024934{col 38}{space 2} .0012125{col 49}{space 1}    2.06{col 58}{space 3}0.040{col 66}{space 4}  .000117{col 79}{space 3} .0048697
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2}-.0033544{col 38}{space 2} .0031052{col 49}{space 1}   -1.08{col 58}{space 3}0.280{col 66}{space 4}-.0094405{col 79}{space 3} .0027316
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .0282663{col 38}{space 2} .0092816{col 49}{space 1}    3.05{col 58}{space 3}0.002{col 66}{space 4} .0100747{col 79}{space 3} .0464579
{txt}{space 12}road_density {c |}{col 26}{res}{space 2}-1.657154{col 38}{space 2} .7556275{col 49}{space 1}   -2.19{col 58}{space 3}0.028{col 66}{space 4}-3.138157{col 79}{space 3}-.1761515
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0159619{col 38}{space 2} .0065593{col 49}{space 1}    2.43{col 58}{space 3}0.015{col 66}{space 4} .0031059{col 79}{space 3} .0288179
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2} .3353148{col 38}{space 2} .1639416{col 49}{space 1}    2.05{col 58}{space 3}0.041{col 66}{space 4} .0139951{col 79}{space 3} .6566345
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2}-.7915157{col 38}{space 2} 1.794202{col 49}{space 1}   -0.44{col 58}{space 3}0.659{col 66}{space 4}-4.308088{col 79}{space 3} 2.725056
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} -2.08155{col 38}{space 2} 1.992829{col 49}{space 1}   -1.04{col 58}{space 3}0.296{col 66}{space 4}-5.987424{col 79}{space 3} 1.824324
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                /lnalpha {c |}{col 26}{res}{space 2}-.8946664{col 38}{space 2} .2787722{col 66}{space 4} -1.44105{col 79}{space 3} -.348283
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   alpha{col 26}{c |}{res}{space 2} .4087439{col 38}{space 2} .1139464{col 66}{space 4} .2366792{col 79}{space 3} .7058991
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Likelihood-ratio test of alpha=0:  {help j_chibar##|_new:chibar2(01) =}{res}   56.06{txt} Prob>=chibar2 = {res}0.000
{txt}
{com}. //Table 2/predicting Maoist Events based on Model 2
. mfx compute, at(mean, bystate_2006= 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 3.2193088
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0080269       .0039    2.06   0.040   .000377  .015677         0
{txt}bym~2006 {c |}  {res}-.0107989         .01   -1.08   0.280  -.030392  .008794   66.2667
{txt}landle~p {c |}  {res}  .090998      .02988    3.05   0.002   .032434  .149562  -.001028
{txt}road_d~y {c |}  {res}-5.334891      2.4326   -2.19   0.028  -10.1027 -.567086   .189921
{txt}gap_in~t {c |}  {res} .0513863      .02112    2.43   0.015   .009999  .092774  -3.7e-06
{txt}ln_~2001 {c |}  {res} 1.079482      .52778    2.05   0.041   .045055  2.11391    12.359
{txt}hdi_2001 {c |}  {res}-2.548134     5.77609   -0.44   0.659  -13.8691   8.7728   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, bystate_2006= 733)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 20.021237
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res}   .04992      .06178    0.81   0.419  -.071161  .171001       733
{txt}bym~2006 {c |}  {res}-.0671597      .10527   -0.64   0.523  -.273489  .139169   66.2667
{txt}landle~p {c |}  {res} .5659267      .47271    1.20   0.231  -.360564  1.49242  -.001028
{txt}road_d~y {c |}  {res}-33.17828      29.032   -1.14   0.253  -90.0808  23.7242   .189921
{txt}gap_in~t {c |}  {res}  .319577      .30243    1.06   0.291   -.27317  .912324  -3.7e-06
{txt}ln_~2001 {c |}  {res} 6.713417      6.5058    1.03   0.302  -6.03771  19.4645    12.359
{txt}hdi_2001 {c |}  {res}-15.84712      37.666   -0.42   0.674  -89.6717  57.9774   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, bymaoist_2006= 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 5.3118701
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0132444      .00868    1.53   0.127  -.003777  .030266   111.693
{txt}bym~2006 {c |}  {res}-.0178183      .02017   -0.88   0.377  -.057353  .021716         0
{txt}landle~p {c |}  {res}  .150147      .06011    2.50   0.012   .032332  .267962  -.001028
{txt}road_d~y {c |}  {res}-8.802588     4.49043   -1.96   0.050  -17.6037 -.001501   .189921
{txt}gap_in~t {c |}  {res} .0847875      .04156    2.04   0.041   .003326  .166249  -3.7e-06
{txt}ln_~2001 {c |}  {res} 1.781149     1.07989    1.65   0.099    -.3354   3.8977    12.359
{txt}hdi_2001 {c |}  {res}-4.204429     9.68833   -0.43   0.664  -23.1932  14.7843   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, bymaoist_2006= 266)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 2.1763891
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0054265       .0023    2.36   0.018   .000916  .009937   111.693
{txt}bym~2006 {c |}  {res}-.0073005      .00231   -3.16   0.002  -.011834 -.002767       266
{txt}landle~p {c |}  {res} .0615185      .04175    1.47   0.141  -.020308  .143345  -.001028
{txt}road_d~y {c |}  {res}-3.606612     2.66606   -1.35   0.176    -8.832  1.61878   .189921
{txt}gap_in~t {c |}  {res} .0347393      .02398    1.45   0.147  -.012258  .081736  -3.7e-06
{txt}ln_~2001 {c |}  {res} .7297755      .44139    1.65   0.098  -.135328  1.59488    12.359
{txt}hdi_2001 {c |}  {res}-1.722646     3.89531   -0.44   0.658  -9.35731  5.91202   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, not_claimedevent = 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 4.2531396
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0106046       .0052    2.04   0.041   .000421  .020788   111.693
{txt}bym~2006 {c |}  {res}-.0142668      .01323   -1.08   0.281  -.040193  .011659   66.2667
{txt}landle~p {c |}  {res} .1202206      .03941    3.05   0.002   .042979  .197463  -.001028
{txt}road_d~y {c |}  {res}-7.048108     3.18266   -2.21   0.027   -13.286  -.81021   .189921
{txt}gap_in~t {c |}  {res} .0678882      .02811    2.41   0.016   .012786  .122991  -3.7e-06
{txt}ln_~2001 {c |}  {res} 1.426141      .69797    2.04   0.041   .058147  2.79413    12.359
{txt}hdi_2001 {c |}  {res}-3.366427      7.6272   -0.44   0.659  -18.3155  11.5826   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, not_claimedevent = 31)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 4.2531396
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0106046       .0052    2.04   0.041   .000421  .020788   111.693
{txt}bym~2006 {c |}  {res}-.0142668      .01323   -1.08   0.281  -.040193  .011659   66.2667
{txt}landle~p {c |}  {res} .1202206      .03941    3.05   0.002   .042979  .197463  -.001028
{txt}road_d~y {c |}  {res}-7.048108     3.18266   -2.21   0.027   -13.286  -.81021   .189921
{txt}gap_in~t {c |}  {res} .0678882      .02811    2.41   0.016   .012786  .122991  -3.7e-06
{txt}ln_~2001 {c |}  {res} 1.426141      .69797    2.04   0.041   .058147  2.79413    12.359
{txt}hdi_2001 {c |}  {res}-3.366427      7.6272   -0.44   0.659  -18.3155  11.5826   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, ethnic_event = 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 4.2531396
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0106046       .0052    2.04   0.041   .000421  .020788   111.693
{txt}bym~2006 {c |}  {res}-.0142668      .01323   -1.08   0.281  -.040193  .011659   66.2667
{txt}landle~p {c |}  {res} .1202206      .03941    3.05   0.002   .042979  .197463  -.001028
{txt}road_d~y {c |}  {res}-7.048108     3.18266   -2.21   0.027   -13.286  -.81021   .189921
{txt}gap_in~t {c |}  {res} .0678882      .02811    2.41   0.016   .012786  .122991  -3.7e-06
{txt}ln_~2001 {c |}  {res} 1.426141      .69797    2.04   0.041   .058147  2.79413    12.359
{txt}hdi_2001 {c |}  {res}-3.366427      7.6272   -0.44   0.659  -18.3155  11.5826   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, ethnic_event = 75)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 4.2531396
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0106046       .0052    2.04   0.041   .000421  .020788   111.693
{txt}bym~2006 {c |}  {res}-.0142668      .01323   -1.08   0.281  -.040193  .011659   66.2667
{txt}landle~p {c |}  {res} .1202206      .03941    3.05   0.002   .042979  .197463  -.001028
{txt}road_d~y {c |}  {res}-7.048108     3.18266   -2.21   0.027   -13.286  -.81021   .189921
{txt}gap_in~t {c |}  {res} .0678882      .02811    2.41   0.016   .012786  .122991  -3.7e-06
{txt}ln_~2001 {c |}  {res} 1.426141      .69797    2.04   0.041   .058147  2.79413    12.359
{txt}hdi_2001 {c |}  {res}-3.366427      7.6272   -0.44   0.659  -18.3155  11.5826   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, landless_gap= -11.684)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 3.0569656
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0076221       .0038    2.01   0.045   .000179  .015066   111.693
{txt}bym~2006 {c |}  {res}-.0102544      .00949   -1.08   0.280  -.028859   .00835   66.2667
{txt}landle~p {c |}  {res} .0864092      .01955    4.42   0.000   .048102  .124717   -11.684
{txt}road_d~y {c |}  {res}-5.065863     1.85766   -2.73   0.006  -8.70681 -1.42491   .189921
{txt}gap_in~t {c |}  {res}  .048795       .0203    2.40   0.016   .009015  .088575  -3.7e-06
{txt}ln_~2001 {c |}  {res} 1.025046       .5381    1.90   0.057  -.029613   2.0797    12.359
{txt}hdi_2001 {c |}  {res}-2.419636     5.44002   -0.44   0.656  -13.0819   8.2426   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, landless_gap= 169.908)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 518.19975
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} 1.292054     2.15382    0.60   0.549  -2.92936  5.51347   111.693
{txt}bym~2006 {c |}  {res}-1.738262     3.27892   -0.53   0.596  -8.16484  4.68831   66.2667
{txt}landle~p {c |}  {res}  14.6476      27.732    0.53   0.597  -39.7055  69.0007   169.908
{txt}road_d~y {c |}  {res}-858.7369      1689.8   -0.51   0.611  -4170.61  2453.14   .189921
{txt}gap_in~t {c |}  {res} 8.271454      13.859    0.60   0.551  -18.8926  35.4355  -3.7e-06
{txt}ln_~2001 {c |}  {res} 173.7601      267.69    0.65   0.516  -350.902  698.422    12.359
{txt}hdi_2001 {c |}  {res}-410.1633      1225.9   -0.33   0.738  -2812.88  1992.55   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, ln_pop2001= 9.168)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.4588981
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0036375      .00237    1.53   0.125  -.001015   .00829   111.693
{txt}bym~2006 {c |}  {res}-.0048938      .00416   -1.18   0.240   -.01305  .003263   66.2667
{txt}landle~p {c |}  {res} .0412377      .02794    1.48   0.140  -.013517  .095992  -.001028
{txt}road_d~y {c |}  {res}-2.417619     1.69358   -1.43   0.153  -5.73697  .901737   .189921
{txt}gap_in~t {c |}  {res} .0232868      .01666    1.40   0.162  -.009369  .055942  -3.7e-06
{txt}ln_~2001 {c |}  {res} .4891902      .05125    9.55   0.000   .388743  .589638     9.168
{txt}hdi_2001 {c |}  {res}-1.154741     2.56769   -0.45   0.653  -6.18732  3.87784   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, ln_pop2001= 13.894)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 7.1162384
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0177433      .01043    1.70   0.089  -.002703   .03819   111.693
{txt}bym~2006 {c |}  {res}-.0238709      .02527   -0.94   0.345  -.073392   .02565   66.2667
{txt}landle~p {c |}  {res} .2011499      .07346    2.74   0.006   .057178  .345122  -.001028
{txt}road_d~y {c |}  {res} -11.7927     6.02366   -1.96   0.050  -23.5989  .013456   .189921
{txt}gap_in~t {c |}  {res} .1135887      .05114    2.22   0.026   .013352  .213825  -3.7e-06
{txt}ln_~2001 {c |}  {res}  2.38618     1.76067    1.36   0.175  -1.06468  5.83704    13.894
{txt}hdi_2001 {c |}  {res}-5.632615      13.112   -0.43   0.668  -31.3318  20.0666   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, hdi_2001= 0.21)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 5.1439524
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0128257      .00829    1.55   0.122  -.003425  .029077   111.693
{txt}bym~2006 {c |}  {res} -.017255      .01858   -0.93   0.353  -.053661  .019151   66.2667
{txt}landle~p {c |}  {res} .1454006      .08532    1.70   0.088  -.021828  .312629  -.001028
{txt}road_d~y {c |}  {res}-8.524322     5.12119   -1.66   0.096  -18.5617  1.51303   .189921
{txt}gap_in~t {c |}  {res} .0821073       .0563    1.46   0.145  -.028247  .192462  -3.7e-06
{txt}ln_~2001 {c |}  {res} 1.724843     1.22752    1.41   0.160  -.681047  4.13073    12.359
{txt}hdi_2001 {c |}  {res}-4.071519      10.978   -0.37   0.711  -25.5889  17.4459       .21
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, hdi_2001= .652)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res}  3.625426
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0090395      .00556    1.63   0.104   -.00185  .019929   111.693
{txt}bym~2006 {c |}  {res}-.0121612      .01151   -1.06   0.291  -.034717  .010394   66.2667
{txt}landle~p {c |}  {res} .1024775      .04532    2.26   0.024   .013646  .191309  -.001028
{txt}road_d~y {c |}  {res} -6.00789     3.60029   -1.67   0.095  -13.0643  1.04855   .189921
{txt}gap_in~t {c |}  {res} .0578687      .02637    2.19   0.028   .006179  .109559  -3.7e-06
{txt}ln_~2001 {c |}  {res} 1.215659      .66852    1.82   0.069  -.094618  2.52594    12.359
{txt}hdi_2001 {c |}  {res}-2.869582     5.46391   -0.53   0.599  -13.5786  7.83948      .652
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, gap_institutional_credit = -22.199)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 2.9841628
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0074406      .00354    2.10   0.035   .000511   .01437   111.693
{txt}bym~2006 {c |}  {res}-.0100101      .00917   -1.09   0.275  -.027978  .007958   66.2667
{txt}landle~p {c |}  {res} .0843513      .02881    2.93   0.003   .027893  .140809  -.001028
{txt}road_d~y {c |}  {res}-4.945218     2.38352   -2.07   0.038  -9.61683 -.273606   .189921
{txt}gap_in~t {c |}  {res} .0476329      .01308    3.64   0.000   .022005  .073261   -22.199
{txt}ln_~2001 {c |}  {res} 1.000634      .53144    1.88   0.060  -.040971  2.04224    12.359
{txt}hdi_2001 {c |}  {res}-2.362012     5.25052   -0.45   0.653  -12.6528  7.92881   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, gap_institutional_credit = 46.481)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 8.9314848
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0222693      .01421    1.57   0.117  -.005586  .050124   111.693
{txt}bym~2006 {c |}  {res}  -.02996      .03057   -0.98   0.327  -.089867  .029947   66.2667
{txt}landle~p {c |}  {res} .2524602      .11992    2.11   0.035    .01742  .487501  -.001028
{txt}road_d~y {c |}  {res}-14.80085     7.85683   -1.88   0.060  -30.1999  .598254   .189921
{txt}gap_in~t {c |}  {res} .1425635      .10183    1.40   0.161  -.057011  .342138    46.481
{txt}ln_~2001 {c |}  {res} 2.994859      1.6066    1.86   0.062  -.154009  6.14373    12.359
{txt}hdi_2001 {c |}  {res}-7.069411      16.837   -0.42   0.675  -40.0698   25.931   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, road_density = 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 5.8263169
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0145271      .00737    1.97   0.049    .00009  .028964   111.693
{txt}bym~2006 {c |}  {res}-.0195439      .01852   -1.06   0.291  -.055842  .016754   66.2667
{txt}landle~p {c |}  {res} .1646886      .07444    2.21   0.027   .018794  .310583  -.001028
{txt}road_d~y {c |}  {res}-9.655105       5.722   -1.69   0.092    -20.87  1.55982         0
{txt}gap_in~t {c |}  {res} .0929991      .03985    2.33   0.020   .014895  .171104  -3.7e-06
{txt}ln_~2001 {c |}  {res}  1.95365      .98623    1.98   0.048   .020675  3.88663    12.359
{txt}hdi_2001 {c |}  {res}-4.611621      10.421   -0.44   0.658  -25.0367  15.8135   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, road_density = 2.0578)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} .19249082
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
bys~2006 {c |}  {res} .0004799      .00072    0.66   0.507  -.000936  .001896   111.693
{txt}bym~2006 {c |}  {res}-.0006457      .00106   -0.61   0.541  -.002717  .001425   66.2667
{txt}landle~p {c |}  {res}  .005441      .00632    0.86   0.389  -.006949  .017831  -.001028
{txt}road_d~y {c |}  {res} -.318987      .31087   -1.03   0.305  -.928273    .2903    2.0578
{txt}gap_in~t {c |}  {res} .0030725      .00461    0.67   0.505  -.005955    .0121  -3.7e-06
{txt}ln_~2001 {c |}  {res}  .064545      .09754    0.66   0.508  -.126624  .255714    12.359
{txt}hdi_2001 {c |}  {res}-.1523595      .41977   -0.36   0.717  -.975089   .67037   .450253
{txt}{hline 9}{c BT}{hline 68}

{com}. 
. //nbreg  maoist_event   bystate_2006 bymaoist_2006 landless_gap  road_density  gap_institutional_credit ln_pop2001 hdi_2001  region_east region_west region_midwest region_farwest
. 
. 
. //Table 2/Model 1&2/FPTP Votes
. reg maoistvote2008_1000 ncvote2008_1000 cpnumlvote2008_1000 no_candidates_2008 maoist_event  bystate_2006 bymaoist_2006  not_claimedevent ethnic_event road_density landless_gap gap_institutional_credit ln_pop2001 hdi_2001, r

{txt}Linear regression                                      Number of obs ={res}      75
                                                       {txt}F( 13,    61) ={res}   49.73
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.6983
                                                       {txt}Root MSE      = {res}  16.44

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}     maoistvote2008_1000{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      t{col 58}   P>|t|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ncvote2008_1000 {c |}{col 26}{res}{space 2}  .360641{col 38}{space 2} .2677404{col 49}{space 1}    1.35{col 58}{space 3}0.183{col 66}{space 4} -.174739{col 79}{space 3} .8960211
{txt}{space 5}cpnumlvote2008_1000 {c |}{col 26}{res}{space 2} .0533562{col 38}{space 2} .3393794{col 49}{space 1}    0.16{col 58}{space 3}0.876{col 66}{space 4} -.625275{col 79}{space 3} .7319873
{txt}{space 6}no_candidates_2008 {c |}{col 26}{res}{space 2}-.0834382{col 38}{space 2} .1001684{col 49}{space 1}   -0.83{col 58}{space 3}0.408{col 66}{space 4}-.2837372{col 79}{space 3} .1168608
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} 1.097658{col 38}{space 2} .5154023{col 49}{space 1}    2.13{col 58}{space 3}0.037{col 66}{space 4} .0670477{col 79}{space 3} 2.128269
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0056762{col 38}{space 2} .0258861{col 49}{space 1}    0.22{col 58}{space 3}0.827{col 66}{space 4}-.0460863{col 79}{space 3} .0574386
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2} .1837955{col 38}{space 2}  .059262{col 49}{space 1}    3.10{col 58}{space 3}0.003{col 66}{space 4} .0652938{col 79}{space 3} .3022971
{txt}{space 8}not_claimedevent {c |}{col 26}{res}{space 2} .4584908{col 38}{space 2} 1.401715{col 49}{space 1}    0.33{col 58}{space 3}0.745{col 66}{space 4}-2.344412{col 79}{space 3} 3.261393
{txt}{space 12}ethnic_event {c |}{col 26}{res}{space 2}-.5251314{col 38}{space 2} .6812777{col 49}{space 1}   -0.77{col 58}{space 3}0.444{col 66}{space 4} -1.88743{col 79}{space 3} .8371676
{txt}{space 12}road_density {c |}{col 26}{res}{space 2}-2.837172{col 38}{space 2} 8.029939{col 49}{space 1}   -0.35{col 58}{space 3}0.725{col 66}{space 4}-18.89403{col 79}{space 3} 13.21968
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .1157352{col 38}{space 2} .2082737{col 49}{space 1}    0.56{col 58}{space 3}0.580{col 66}{space 4}-.3007339{col 79}{space 3} .5322043
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0287224{col 38}{space 2} .1549705{col 49}{space 1}    0.19{col 58}{space 3}0.854{col 66}{space 4}-.2811602{col 79}{space 3} .3386051
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2} 8.832751{col 38}{space 2} 5.371547{col 49}{space 1}    1.64{col 58}{space 3}0.105{col 66}{space 4} -1.90832{col 79}{space 3} 19.57382
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2} 26.29946{col 38}{space 2}  31.1089{col 49}{space 1}    0.85{col 58}{space 3}0.401{col 66}{space 4}-35.90664{col 79}{space 3} 88.50556
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} -104.123{col 38}{space 2} 59.87794{col 49}{space 1}   -1.74{col 58}{space 3}0.087{col 66}{space 4}-223.8564{col 79}{space 3} 15.61031
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg maoistvote2008_1000 ncvote2008_1000 cpnumlvote2008_1000 no_candidates_2008 maoist_event  bystate_2006 bymaoist_2006  landless_gap gap_institutional_credit ln_pop2001 hdi_2001, r

{txt}Linear regression                                      Number of obs ={res}      75
                                                       {txt}F( 10,    64) ={res}   63.59
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.6898
                                                       {txt}Root MSE      = {res} 16.275

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}     maoistvote2008_1000{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      t{col 58}   P>|t|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ncvote2008_1000 {c |}{col 26}{res}{space 2} .4338508{col 38}{space 2} .2689211{col 49}{space 1}    1.61{col 58}{space 3}0.112{col 66}{space 4}-.1033809{col 79}{space 3} .9710826
{txt}{space 5}cpnumlvote2008_1000 {c |}{col 26}{res}{space 2} .0873008{col 38}{space 2} .3185774{col 49}{space 1}    0.27{col 58}{space 3}0.785{col 66}{space 4}-.5491308{col 79}{space 3} .7237323
{txt}{space 6}no_candidates_2008 {c |}{col 26}{res}{space 2}-.1788264{col 38}{space 2} .0644508{col 49}{space 1}   -2.77{col 58}{space 3}0.007{col 66}{space 4}-.3075817{col 79}{space 3} -.050071
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} 1.172596{col 38}{space 2} .4719301{col 49}{space 1}    2.48{col 58}{space 3}0.016{col 66}{space 4} .2298076{col 79}{space 3} 2.115385
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0046184{col 38}{space 2} .0250447{col 49}{space 1}    0.18{col 58}{space 3}0.854{col 66}{space 4}-.0454141{col 79}{space 3} .0546508
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2} .2006931{col 38}{space 2} .0609985{col 49}{space 1}    3.29{col 58}{space 3}0.002{col 66}{space 4} .0788346{col 79}{space 3} .3225516
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .1848661{col 38}{space 2} .1583799{col 49}{space 1}    1.17{col 58}{space 3}0.247{col 66}{space 4}-.1315341{col 79}{space 3} .5012663
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0133487{col 38}{space 2} .1503857{col 49}{space 1}    0.09{col 58}{space 3}0.930{col 66}{space 4}-.2870812{col 79}{space 3} .3137786
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2}   7.8126{col 38}{space 2} 4.483505{col 49}{space 1}    1.74{col 58}{space 3}0.086{col 66}{space 4}-1.144232{col 79}{space 3} 16.76943
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2} 27.88286{col 38}{space 2} 29.10202{col 49}{space 1}    0.96{col 58}{space 3}0.342{col 66}{space 4}-30.25511{col 79}{space 3} 86.02084
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-93.56656{col 38}{space 2} 49.92068{col 49}{space 1}   -1.87{col 58}{space 3}0.065{col 66}{space 4}-193.2946{col 79}{space 3} 6.161471
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. //Table 2/Model 3&4/PR Votes
. reg prv_maoist2008_1000 prv_nc2008_1000 prv_uml2008_1000 maoist_event  bystate_2006 bymaoist_2006  not_claimedevent ethnic_event road_density landless_gap gap_institutional_credit ln_pop2001 hdi_2001, r

{txt}Linear regression                                      Number of obs ={res}      75
                                                       {txt}F( 12,    62) ={res}   15.04
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.5757
                                                       {txt}Root MSE      = {res} 19.697

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}     prv_maoist2008_1000{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      t{col 58}   P>|t|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}prv_nc2008_1000 {c |}{col 26}{res}{space 2} 1.024941{col 38}{space 2} .1256405{col 49}{space 1}    8.16{col 58}{space 3}0.000{col 66}{space 4}  .773789{col 79}{space 3} 1.276093
{txt}{space 8}prv_uml2008_1000 {c |}{col 26}{res}{space 2}-.0382949{col 38}{space 2} .0726392{col 49}{space 1}   -0.53{col 58}{space 3}0.600{col 66}{space 4}-.1834986{col 79}{space 3} .1069088
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} .9899354{col 38}{space 2} .4553919{col 49}{space 1}    2.17{col 58}{space 3}0.034{col 66}{space 4} .0796199{col 79}{space 3} 1.900251
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0244669{col 38}{space 2} .0226237{col 49}{space 1}    1.08{col 58}{space 3}0.284{col 66}{space 4}-.0207572{col 79}{space 3}  .069691
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2}  .075514{col 38}{space 2} .0604631{col 49}{space 1}    1.25{col 58}{space 3}0.216{col 66}{space 4}  -.04535{col 79}{space 3} .1963781
{txt}{space 8}not_claimedevent {c |}{col 26}{res}{space 2}-1.936469{col 38}{space 2} 2.419492{col 49}{space 1}   -0.80{col 58}{space 3}0.427{col 66}{space 4}-6.772966{col 79}{space 3} 2.900027
{txt}{space 12}ethnic_event {c |}{col 26}{res}{space 2} .8821729{col 38}{space 2} .9601776{col 49}{space 1}    0.92{col 58}{space 3}0.362{col 66}{space 4}-1.037195{col 79}{space 3} 2.801541
{txt}{space 12}road_density {c |}{col 26}{res}{space 2} 13.54718{col 38}{space 2} 15.66825{col 49}{space 1}    0.86{col 58}{space 3}0.391{col 66}{space 4} -17.7732{col 79}{space 3} 44.86756
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2}  .072432{col 38}{space 2} .1981083{col 49}{space 1}    0.37{col 58}{space 3}0.716{col 66}{space 4}-.3235809{col 79}{space 3} .4684449
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0173137{col 38}{space 2} .1339922{col 49}{space 1}    0.13{col 58}{space 3}0.898{col 66}{space 4}-.2505329{col 79}{space 3} .2851603
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2}-6.799181{col 38}{space 2}  2.84151{col 49}{space 1}   -2.39{col 58}{space 3}0.020{col 66}{space 4}-12.47928{col 79}{space 3}-1.119083
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2}-24.72677{col 38}{space 2} 51.54838{col 49}{space 1}   -0.48{col 58}{space 3}0.633{col 66}{space 4}-127.7705{col 79}{space 3} 78.31697
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} 92.52287{col 38}{space 2} 40.34952{col 49}{space 1}    2.29{col 58}{space 3}0.025{col 66}{space 4} 11.86534{col 79}{space 3} 173.1804
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg prv_maoist2008_1000 prv_nc2008_1000 prv_uml2008_1000 maoist_event  bystate_2006 bymaoist_2006  landless_gap gap_institutional_credit ln_pop2001 hdi_2001, r

{txt}Linear regression                                      Number of obs ={res}      75
                                                       {txt}F(  9,    65) ={res}   14.42
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.5620
                                                       {txt}Root MSE      = {res} 19.544

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}     prv_maoist2008_1000{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      t{col 58}   P>|t|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}prv_nc2008_1000 {c |}{col 26}{res}{space 2} 1.045363{col 38}{space 2} .1273384{col 49}{space 1}    8.21{col 58}{space 3}0.000{col 66}{space 4} .7910511{col 79}{space 3} 1.299676
{txt}{space 8}prv_uml2008_1000 {c |}{col 26}{res}{space 2}-.0613091{col 38}{space 2} .0657735{col 49}{space 1}   -0.93{col 58}{space 3}0.355{col 66}{space 4}-.1926679{col 79}{space 3} .0700498
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} .8545233{col 38}{space 2} .4299176{col 49}{space 1}    1.99{col 58}{space 3}0.051{col 66}{space 4}-.0040815{col 79}{space 3} 1.713128
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2} .0174519{col 38}{space 2} .0220708{col 49}{space 1}    0.79{col 58}{space 3}0.432{col 66}{space 4}-.0266266{col 79}{space 3} .0615304
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2} .0653145{col 38}{space 2} .0635997{col 49}{space 1}    1.03{col 58}{space 3}0.308{col 66}{space 4} -.061703{col 79}{space 3} .1923319
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .1667823{col 38}{space 2} .1091076{col 49}{space 1}    1.53{col 58}{space 3}0.131{col 66}{space 4}-.0511205{col 79}{space 3} .3846852
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2} .0014731{col 38}{space 2} .1320876{col 49}{space 1}    0.01{col 58}{space 3}0.991{col 66}{space 4} -.262324{col 79}{space 3} .2652702
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2}-5.748483{col 38}{space 2} 2.717006{col 49}{space 1}   -2.12{col 58}{space 3}0.038{col 66}{space 4}-11.17472{col 79}{space 3}-.3222469
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2}-21.26701{col 38}{space 2} 50.29809{col 49}{space 1}   -0.42{col 58}{space 3}0.674{col 66}{space 4}-121.7192{col 79}{space 3} 79.18521
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} 82.24554{col 38}{space 2} 40.70458{col 49}{space 1}    2.02{col 58}{space 3}0.047{col 66}{space 4} .9528694{col 79}{space 3} 163.5382
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. //Table 3/FPTP Seats/Maoist
. nbreg seat_cpnm_2008 seat_nc2008 seat_cpnuml_2008 landless_gap no_candidates_2008 maoist_event   not_claimedevent ethnic_event   bystate_2006  bymaoist_2006 ln_pop2001 hdi_2001 gap_institutional_credit, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-93.482714}  
Iteration 1:{space 3}log pseudolikelihood = {res:-93.440336}  
Iteration 2:{space 3}log pseudolikelihood = {res:-93.440252}  
Iteration 3:{space 3}log pseudolikelihood = {res:-93.440252}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -129.9243}  
Iteration 1:{space 3}log pseudolikelihood = {res:-120.46267}  
Iteration 2:{space 3}log pseudolikelihood = {res:-120.43803}  
Iteration 3:{space 3}log pseudolikelihood = {res:-120.43678}  
Iteration 4:{space 3}log pseudolikelihood = {res:-120.43678}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-99.588123}  
Iteration 1:{space 3}log pseudolikelihood = {res:-94.157872}  
Iteration 2:{space 3}log pseudolikelihood = {res:-93.605992}  
Iteration 3:{space 3}log pseudolikelihood = {res:-93.472168}  
Iteration 4:{space 3}log pseudolikelihood = {res: -93.44746}  
Iteration 5:{space 3}log pseudolikelihood = {res:-93.441924}  
Iteration 6:{space 3}log pseudolikelihood = {res:-93.440618}  
Iteration 7:{space 3}log pseudolikelihood = {res:-93.440328}  
Iteration 8:{space 3}log pseudolikelihood = {res:-93.440264}  
Iteration 9:{space 3}log pseudolikelihood = {res:-93.440252}  
Iteration 10:{space 2}log pseudolikelihood = {res:-93.440252}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}12{txt})   =  {res}   330.34
{txt}Log pseudolikelihood = {res}-93.440252                 {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}          seat_cpnm_2008{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}seat_nc2008 {c |}{col 26}{res}{space 2}-.4275442{col 38}{space 2} .1195831{col 49}{space 1}   -3.58{col 58}{space 3}0.000{col 66}{space 4}-.6619228{col 79}{space 3}-.1931657
{txt}{space 8}seat_cpnuml_2008 {c |}{col 26}{res}{space 2}-.5838637{col 38}{space 2} .1157322{col 49}{space 1}   -5.04{col 58}{space 3}0.000{col 66}{space 4}-.8106947{col 79}{space 3}-.3570328
{txt}{space 12}landless_gap {c |}{col 26}{res}{space 2} .0019608{col 38}{space 2} .0064027{col 49}{space 1}    0.31{col 58}{space 3}0.759{col 66}{space 4}-.0105882{col 79}{space 3} .0145099
{txt}{space 6}no_candidates_2008 {c |}{col 26}{res}{space 2} .0029518{col 38}{space 2} .0048706{col 49}{space 1}    0.61{col 58}{space 3}0.544{col 66}{space 4}-.0065944{col 79}{space 3} .0124981
{txt}{space 12}maoist_event {c |}{col 26}{res}{space 2} .0263584{col 38}{space 2} .0126982{col 49}{space 1}    2.08{col 58}{space 3}0.038{col 66}{space 4} .0014704{col 79}{space 3} .0512464
{txt}{space 8}not_claimedevent {c |}{col 26}{res}{space 2}   .14056{col 38}{space 2} .0836245{col 49}{space 1}    1.68{col 58}{space 3}0.093{col 66}{space 4} -.023341{col 79}{space 3} .3044611
{txt}{space 12}ethnic_event {c |}{col 26}{res}{space 2}-.1016552{col 38}{space 2} .0441078{col 49}{space 1}   -2.30{col 58}{space 3}0.021{col 66}{space 4} -.188105{col 79}{space 3}-.0152054
{txt}{space 12}bystate_2006 {c |}{col 26}{res}{space 2}-.0007445{col 38}{space 2} .0006407{col 49}{space 1}   -1.16{col 58}{space 3}0.245{col 66}{space 4}-.0020003{col 79}{space 3} .0005112
{txt}{space 11}bymaoist_2006 {c |}{col 26}{res}{space 2} .0018903{col 38}{space 2} .0016553{col 49}{space 1}    1.14{col 58}{space 3}0.253{col 66}{space 4}-.0013541{col 79}{space 3} .0051346
{txt}{space 14}ln_pop2001 {c |}{col 26}{res}{space 2} .5438492{col 38}{space 2} .2084957{col 49}{space 1}    2.61{col 58}{space 3}0.009{col 66}{space 4} .1352052{col 79}{space 3} .9524932
{txt}{space 16}hdi_2001 {c |}{col 26}{res}{space 2} .4276686{col 38}{space 2} 1.287498{col 49}{space 1}    0.33{col 58}{space 3}0.740{col 66}{space 4}-2.095782{col 79}{space 3} 2.951119
{txt}gap_institutional_credit {c |}{col 26}{res}{space 2}-.0017014{col 38}{space 2}  .003985{col 49}{space 1}   -0.43{col 58}{space 3}0.669{col 66}{space 4}-.0095119{col 79}{space 3}  .006109
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-6.453059{col 38}{space 2} 2.281513{col 49}{space 1}   -2.83{col 58}{space 3}0.005{col 66}{space 4}-10.92474{col 79}{space 3}-1.981376
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                /lnalpha {c |}{col 26}{res}{space 2}-21.23982{col 38}{space 2}        .{col 66}{space 4}        .{col 79}{space 3}        .
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   alpha{col 26}{c |}{res}{space 2} 5.97e-10{col 38}{space 2}        .{col 66}{space 4}        .{col 79}{space 3}        .
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. nbreg seat_cpnm_2008 seat_nc2008 seat_cpnuml_2008 road_density maoist_event   ethnic_event   bystate_2006  bymaoist_2006 ln_pop2001 hdi_2001, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-95.696074}  
Iteration 1:{space 3}log pseudolikelihood = {res: -95.68644}  
Iteration 2:{space 3}log pseudolikelihood = {res:-95.686439}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -129.9243}  
Iteration 1:{space 3}log pseudolikelihood = {res:-120.46267}  
Iteration 2:{space 3}log pseudolikelihood = {res:-120.43803}  
Iteration 3:{space 3}log pseudolikelihood = {res:-120.43678}  
Iteration 4:{space 3}log pseudolikelihood = {res:-120.43678}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-101.30665}  
Iteration 1:{space 3}log pseudolikelihood = {res:-96.333034}  
Iteration 2:{space 3}log pseudolikelihood = {res:-95.842129}  
Iteration 3:{space 3}log pseudolikelihood = {res:-95.721337}  
Iteration 4:{space 3}log pseudolikelihood = {res:-95.694766}  
Iteration 5:{space 3}log pseudolikelihood = {res:-95.688145}  
Iteration 6:{space 3}log pseudolikelihood = {res:-95.686811}  
Iteration 7:{space 3}log pseudolikelihood = {res:-95.686524}  
Iteration 8:{space 3}log pseudolikelihood = {res:-95.686459}  
Iteration 9:{space 3}log pseudolikelihood = {res:-95.686443}  
Iteration 10:{space 2}log pseudolikelihood = {res:-95.686439}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}9{txt})    =  {res}   116.81
{txt}Log pseudolikelihood = {res}-95.686439                 {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  seat_cpnm_2008{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}seat_nc2008 {c |}{col 18}{res}{space 2}-.2299514{col 30}{space 2} .0980717{col 41}{space 1}   -2.34{col 50}{space 3}0.019{col 58}{space 4}-.4221683{col 71}{space 3}-.0377344
{txt}seat_cpnuml_2008 {c |}{col 18}{res}{space 2}-.5948972{col 30}{space 2} .1209234{col 41}{space 1}   -4.92{col 50}{space 3}0.000{col 58}{space 4}-.8319027{col 71}{space 3}-.3578918
{txt}{space 4}road_density {c |}{col 18}{res}{space 2}-.0943229{col 30}{space 2} .3589099{col 41}{space 1}   -0.26{col 50}{space 3}0.793{col 58}{space 4}-.7977733{col 71}{space 3} .6091275
{txt}{space 4}maoist_event {c |}{col 18}{res}{space 2} .0325293{col 30}{space 2} .0120868{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0088397{col 71}{space 3}  .056219
{txt}{space 4}ethnic_event {c |}{col 18}{res}{space 2}-.0329699{col 30}{space 2} .0091883{col 41}{space 1}   -3.59{col 50}{space 3}0.000{col 58}{space 4}-.0509785{col 71}{space 3}-.0149612
{txt}{space 4}bystate_2006 {c |}{col 18}{res}{space 2}-.0002673{col 30}{space 2} .0006003{col 41}{space 1}   -0.45{col 50}{space 3}0.656{col 58}{space 4}-.0014439{col 71}{space 3} .0009093
{txt}{space 3}bymaoist_2006 {c |}{col 18}{res}{space 2} .0022309{col 30}{space 2} .0015666{col 41}{space 1}    1.42{col 50}{space 3}0.154{col 58}{space 4}-.0008396{col 71}{space 3} .0053015
{txt}{space 6}ln_pop2001 {c |}{col 18}{res}{space 2} .6603768{col 30}{space 2} .1925877{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} .2829118{col 71}{space 3} 1.037842
{txt}{space 8}hdi_2001 {c |}{col 18}{res}{space 2} 1.629083{col 30}{space 2} 1.248234{col 41}{space 1}    1.31{col 50}{space 3}0.192{col 58}{space 4}  -.81741{col 71}{space 3} 4.075576
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-8.425289{col 30}{space 2} 2.105937{col 41}{space 1}   -4.00{col 50}{space 3}0.000{col 58}{space 4}-12.55285{col 71}{space 3}-4.297728
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /lnalpha {c |}{col 18}{res}{space 2}-17.10573{col 30}{space 2} .0946562{col 58}{space 4}-17.29125{col 71}{space 3} -16.9202
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           alpha{col 18}{c |}{res}{space 2} 3.72e-08{col 30}{space 2} 3.53e-09{col 58}{space 4} 3.09e-08{col 71}{space 3} 4.48e-08
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. nbreg seat_cpnm_2008 seat_nc2008 seat_cpnuml_2008 road_density maoist_event   bystate_2006  bymaoist_2006 ln_pop2001, r

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-101.67337}  
Iteration 1:{space 3}log pseudolikelihood = {res:-101.67102}  
Iteration 2:{space 3}log pseudolikelihood = {res:-101.67102}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -129.9243}  
Iteration 1:{space 3}log pseudolikelihood = {res:-120.46267}  
Iteration 2:{space 3}log pseudolikelihood = {res:-120.43803}  
Iteration 3:{space 3}log pseudolikelihood = {res:-120.43678}  
Iteration 4:{space 3}log pseudolikelihood = {res:-120.43678}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-104.87755}  
Iteration 1:{space 3}log pseudolikelihood = {res:-102.16835}  
Iteration 2:{space 3}log pseudolikelihood = {res:-101.78049}  
Iteration 3:{space 3}log pseudolikelihood = {res:-101.69379}  
Iteration 4:{space 3}log pseudolikelihood = {res:-101.67624}  
Iteration 5:{space 3}log pseudolikelihood = {res:-101.67225}  
Iteration 6:{space 3}log pseudolikelihood = {res:-101.67127}  
Iteration 7:{space 3}log pseudolikelihood = {res:-101.67107}  
Iteration 8:{space 3}log pseudolikelihood = {res:-101.67103}  
Iteration 9:{space 3}log pseudolikelihood = {res:-101.67102}  
{res}
{txt}Negative binomial regression                      Number of obs   =  {res}       75
{txt}Dispersion           = {res}mean                       {txt}Wald chi2({res}7{txt})    =  {res}    90.76
{txt}Log pseudolikelihood = {res}-101.67102                 {txt}Prob > chi2     =  {res}   0.0000

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  seat_cpnm_2008{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}seat_nc2008 {c |}{col 18}{res}{space 2}-.2159198{col 30}{space 2} .1017982{col 41}{space 1}   -2.12{col 50}{space 3}0.034{col 58}{space 4}-.4154406{col 71}{space 3}-.0163989
{txt}seat_cpnuml_2008 {c |}{col 18}{res}{space 2}-.4753914{col 30}{space 2} .1369399{col 41}{space 1}   -3.47{col 50}{space 3}0.001{col 58}{space 4}-.7437887{col 71}{space 3}-.2069942
{txt}{space 4}road_density {c |}{col 18}{res}{space 2} .2383199{col 30}{space 2} .3511324{col 41}{space 1}    0.68{col 50}{space 3}0.497{col 58}{space 4}-.4498869{col 71}{space 3} .9265268
{txt}{space 4}maoist_event {c |}{col 18}{res}{space 2} .0389933{col 30}{space 2} .0136589{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0122223{col 71}{space 3} .0657643
{txt}{space 4}bystate_2006 {c |}{col 18}{res}{space 2}-.0004199{col 30}{space 2} .0006843{col 41}{space 1}   -0.61{col 50}{space 3}0.539{col 58}{space 4}-.0017611{col 71}{space 3} .0009213
{txt}{space 3}bymaoist_2006 {c |}{col 18}{res}{space 2} .0037557{col 30}{space 2}  .001674{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0004748{col 71}{space 3} .0070366
{txt}{space 6}ln_pop2001 {c |}{col 18}{res}{space 2} .3829613{col 30}{space 2} .1488593{col 41}{space 1}    2.57{col 50}{space 3}0.010{col 58}{space 4} .0912025{col 71}{space 3} .6747201
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-4.565937{col 30}{space 2} 1.740187{col 41}{space 1}   -2.62{col 50}{space 3}0.009{col 58}{space 4} -7.97664{col 71}{space 3}-1.155234
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /lnalpha {c |}{col 18}{res}{space 2}-16.43882{col 30}{space 2} .7932794{col 58}{space 4}-17.99362{col 71}{space 3}-14.88402
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           alpha{col 18}{c |}{res}{space 2} 7.26e-08{col 30}{space 2} 5.76e-08{col 58}{space 4} 1.53e-08{col 71}{space 3} 3.44e-07
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. //Prediction of Seats based on Model 2 in Table 3
. 
. 
. mfx compute, at(mean, maoist_event=0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.1106565
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.2398127      .11536   -2.08   0.038  -.465914 -.013711   .493333
{txt}s~l_2008 {c |}  {res}-.5279966      .15702   -3.36   0.001  -.835758 -.220235   .426667
{txt}road_d~y {c |}  {res} .2646916      .39511    0.67   0.503  -.509709  1.03909   .189921
{txt}maoist~t {c |}  {res} .0433082      .01165    3.72   0.000   .020477   .06614         0
{txt}bys~2006 {c |}  {res}-.0004664      .00076   -0.61   0.540  -.001957  .001024   111.693
{txt}bym~2006 {c |}  {res} .0041713      .00187    2.23   0.026   .000508  .007835   66.2667
{txt}ln_~2001 {c |}  {res} .4253385      .18311    2.32   0.020   .066459  .784218    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, maoist_event=26)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 3.0611107
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.6609544      .36642   -1.80   0.071  -1.37912  .057216   .493333
{txt}s~l_2008 {c |}  {res}-1.455226      .49168   -2.96   0.003   -2.4189 -.491556   .426667
{txt}road_d~y {c |}  {res} .7295237     1.06587    0.68   0.494  -1.35954  2.81859   .189921
{txt}maoist~t {c |}  {res} .1193629      .07385    1.62   0.106  -.025375  .264101        26
{txt}bys~2006 {c |}  {res}-.0012854       .0022   -0.58   0.559  -.005593  .003022   111.693
{txt}bym~2006 {c |}  {res} .0114966      .00629    1.83   0.068  -.000839  .023832   66.2667
{txt}ln_~2001 {c |}  {res} 1.172287      .49033    2.39   0.017   .211259  2.13331    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. //mfx compute, at(mean, not_claimedevent= 0)
. //mfx compute, at(mean, not_claimedevent= 31)
. mfx compute, at(mean, ethnic_event = 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.3518549
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.2918922      .13889   -2.10   0.036  -.564112 -.019673   .493333
{txt}s~l_2008 {c |}  {res}-.6426602      .17449   -3.68   0.000  -.984654 -.300667   .426667
{txt}road_d~y {c |}  {res}  .322174      .47681    0.68   0.499  -.612363  1.25671   .189921
{txt}maoist~t {c |}  {res} .0527133       .0177    2.98   0.003   .018012  .087414      5.04
{txt}bys~2006 {c |}  {res}-.0005677      .00093   -0.61   0.542  -.002392  .001257   111.693
{txt}bym~2006 {c |}  {res} .0050772      .00227    2.23   0.025   .000624   .00953   66.2667
{txt}ln_~2001 {c |}  {res} .5177081       .2094    2.47   0.013    .10729  .928126    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, ethnic_event = 75)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.3518549
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.2918922      .13889   -2.10   0.036  -.564112 -.019673   .493333
{txt}s~l_2008 {c |}  {res}-.6426602      .17449   -3.68   0.000  -.984654 -.300667   .426667
{txt}road_d~y {c |}  {res}  .322174      .47681    0.68   0.499  -.612363  1.25671   .189921
{txt}maoist~t {c |}  {res} .0527133       .0177    2.98   0.003   .018012  .087414      5.04
{txt}bys~2006 {c |}  {res}-.0005677      .00093   -0.61   0.542  -.002392  .001257   111.693
{txt}bym~2006 {c |}  {res} .0050772      .00227    2.23   0.025   .000624   .00953   66.2667
{txt}ln_~2001 {c |}  {res} .5177081       .2094    2.47   0.013    .10729  .928126    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, seat_nc2008 = 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.5038042
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.3247011      .17063   -1.90   0.057  -.659125  .009723         0
{txt}s~l_2008 {c |}  {res}-.7148957      .19964   -3.58   0.000  -1.10619 -.323601   .426667
{txt}road_d~y {c |}  {res} .3583865      .54261    0.66   0.509  -.705119  1.42189   .189921
{txt}maoist~t {c |}  {res} .0586383      .02003    2.93   0.003   .019379  .097898      5.04
{txt}bys~2006 {c |}  {res}-.0006315      .00103   -0.61   0.541  -.002657  .001394   111.693
{txt}bym~2006 {c |}  {res} .0056479      .00247    2.29   0.022   .000805   .01049   66.2667
{txt}ln_~2001 {c |}  {res} .5758989      .24009    2.40   0.016   .105321  1.04648    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, seat_nc2008 = 6)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} .41167518
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.0888888      .01041   -8.54   0.000  -.109297 -.068481         6
{txt}s~l_2008 {c |}  {res}-.1957069       .1188   -1.65   0.099  -.428541  .037127   .426667
{txt}road_d~y {c |}  {res} .0981104      .11586    0.85   0.397  -.128962  .325183   .189921
{txt}maoist~t {c |}  {res} .0160526       .0103    1.56   0.119   -.00414  .036245      5.04
{txt}bys~2006 {c |}  {res}-.0001729      .00031   -0.56   0.574  -.000775   .00043   111.693
{txt}bym~2006 {c |}  {res} .0015461      .00124    1.25   0.212  -.000882  .003974   66.2667
{txt}ln_~2001 {c |}  {res} .1576557      .09872    1.60   0.110  -.035822  .351134    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, seat_cpnuml_2008 = 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.6558448
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.3575296      .17163   -2.08   0.037  -.693913 -.021146   .493333
{txt}s~l_2008 {c |}  {res}-.7871744      .25845   -3.05   0.002  -1.29372 -.280625         0
{txt}road_d~y {c |}  {res} .3946208      .58258    0.68   0.498  -.747212  1.53645   .189921
{txt}maoist~t {c |}  {res} .0645669      .02103    3.07   0.002   .023357  .105777      5.04
{txt}bys~2006 {c |}  {res}-.0006953      .00114   -0.61   0.542  -.002929  .001539   111.693
{txt}bym~2006 {c |}  {res} .0062189      .00274    2.27   0.023   .000854  .011584   66.2667
{txt}ln_~2001 {c |}  {res} .6341245      .26455    2.40   0.017   .115622  1.15263    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, seat_cpnuml_2008 = 2)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} .63988196
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.1381632      .07187   -1.92   0.055  -.279022  .002696   .493333
{txt}s~l_2008 {c |}  {res}-.3041944      .02557  -11.90   0.000  -.354315 -.254074         2
{txt}road_d~y {c |}  {res} .1524966      .23075    0.66   0.509  -.299761  .604754   .189921
{txt}maoist~t {c |}  {res} .0249511      .01107    2.25   0.024   .003259  .046643      5.04
{txt}bys~2006 {c |}  {res}-.0002687      .00045   -0.60   0.547  -.001144  .000606   111.693
{txt}bym~2006 {c |}  {res} .0024032      .00128    1.88   0.060  -.000104   .00491   66.2667
{txt}ln_~2001 {c |}  {res}   .24505      .10515    2.33   0.020   .038969  .451131    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, bystate_2006= 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.4167688
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.3059084      .14589   -2.10   0.036  -.591844 -.019973   .493333
{txt}s~l_2008 {c |}  {res}-.6735198      .19069   -3.53   0.000  -1.04727 -.299772   .426667
{txt}road_d~y {c |}  {res} .3376442      .49632    0.68   0.496  -.635133  1.31042   .189921
{txt}maoist~t {c |}  {res} .0552445      .01987    2.78   0.005   .016295  .094194      5.04
{txt}bys~2006 {c |}  {res}-.0005949      .00102   -0.58   0.560  -.002596  .001407         0
{txt}bym~2006 {c |}  {res}  .005321      .00273    1.95   0.051  -.000021  .010662   66.2667
{txt}ln_~2001 {c |}  {res} .5425677      .21734    2.50   0.013   .116593  .968542    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, bystate_2006= 733)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.0414196
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.2248631      .14813   -1.52   0.129  -.515196   .06547   .493333
{txt}s~l_2008 {c |}  {res}-.4950819       .2481   -2.00   0.046  -.981354  -.00881   .426667
{txt}road_d~y {c |}  {res}  .248191      .39774    0.62   0.533   -.53136  1.02774   .189921
{txt}maoist~t {c |}  {res} .0406084      .01964    2.07   0.039   .002124  .079093      5.04
{txt}bys~2006 {c |}  {res}-.0004373      .00053   -0.82   0.411  -.001479  .000605       733
{txt}bym~2006 {c |}  {res} .0039113      .00102    3.83   0.000   .001909  .005914   66.2667
{txt}ln_~2001 {c |}  {res} .3988234      .25045    1.59   0.111  -.092044  .889691    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, bymaoist_2006= 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.0540072
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res} -.227581      .11737   -1.94   0.053   -.45763  .002468   .493333
{txt}s~l_2008 {c |}  {res} -.501066      .15486   -3.24   0.001  -.804593 -.197539   .426667
{txt}road_d~y {c |}  {res} .2511909      .37558    0.67   0.504  -.484931  .987313   .189921
{txt}maoist~t {c |}  {res} .0410992      .01405    2.92   0.003   .013553  .068646      5.04
{txt}bys~2006 {c |}  {res}-.0004426      .00069   -0.64   0.520   -.00179  .000905   111.693
{txt}bym~2006 {c |}  {res} .0039585      .00134    2.95   0.003   .001331  .006586         0
{txt}ln_~2001 {c |}  {res}  .403644      .18766    2.15   0.031    .03583  .771458    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, bymaoist_2006= 266)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res}  2.862279
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.6180227      .31269   -1.98   0.048  -1.23088 -.005163   .493333
{txt}s~l_2008 {c |}  {res}-1.360703      .53895   -2.52   0.012  -2.41703 -.304378   .426667
{txt}road_d~y {c |}  {res} .6821381     1.01243    0.67   0.500  -1.30219  2.66647   .189921
{txt}maoist~t {c |}  {res} .1116098      .05572    2.00   0.045   .002399   .22082      5.04
{txt}bys~2006 {c |}  {res}-.0012019       .0023   -0.52   0.602  -.005719  .003315   111.693
{txt}bym~2006 {c |}  {res} .0107499      .00838    1.28   0.199  -.005668  .027167       266
{txt}ln_~2001 {c |}  {res} 1.096142      .43027    2.55   0.011   .252831  1.93945    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, hdi_2001= 0.21)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.3518549
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.2918922      .13889   -2.10   0.036  -.564112 -.019673   .493333
{txt}s~l_2008 {c |}  {res}-.6426602      .17449   -3.68   0.000  -.984654 -.300667   .426667
{txt}road_d~y {c |}  {res}  .322174      .47681    0.68   0.499  -.612363  1.25671   .189921
{txt}maoist~t {c |}  {res} .0527133       .0177    2.98   0.003   .018012  .087414      5.04
{txt}bys~2006 {c |}  {res}-.0005677      .00093   -0.61   0.542  -.002392  .001257   111.693
{txt}bym~2006 {c |}  {res} .0050772      .00227    2.23   0.025   .000624   .00953   66.2667
{txt}ln_~2001 {c |}  {res} .5177081       .2094    2.47   0.013    .10729  .928126    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, hdi_2001= .652)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.3518549
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.2918922      .13889   -2.10   0.036  -.564112 -.019673   .493333
{txt}s~l_2008 {c |}  {res}-.6426602      .17449   -3.68   0.000  -.984654 -.300667   .426667
{txt}road_d~y {c |}  {res}  .322174      .47681    0.68   0.499  -.612363  1.25671   .189921
{txt}maoist~t {c |}  {res} .0527133       .0177    2.98   0.003   .018012  .087414      5.04
{txt}bys~2006 {c |}  {res}-.0005677      .00093   -0.61   0.542  -.002392  .001257   111.693
{txt}bym~2006 {c |}  {res} .0050772      .00227    2.23   0.025   .000624   .00953   66.2667
{txt}ln_~2001 {c |}  {res} .5177081       .2094    2.47   0.013    .10729  .928126    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, ln_pop2001= 9.168)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} .39830531
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res} -.086002      .05114   -1.68   0.093  -.186241  .014237   .493333
{txt}s~l_2008 {c |}  {res}-.1893509      .09089   -2.08   0.037  -.367493 -.011209   .426667
{txt}road_d~y {c |}  {res} .0949241      .15783    0.60   0.548  -.214414  .404262   .189921
{txt}maoist~t {c |}  {res} .0155313      .01003    1.55   0.121  -.004118   .03518      5.04
{txt}bys~2006 {c |}  {res}-.0001673       .0003   -0.56   0.575  -.000752  .000417   111.693
{txt}bym~2006 {c |}  {res} .0014959      .00117    1.28   0.200  -.000794  .003786   66.2667
{txt}ln_~2001 {c |}  {res} .1525355       .0163    9.36   0.000   .120595  .184476     9.168
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, ln_pop2001= 13.894)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res}   2.43352
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.5254451      .29999   -1.75   0.080  -1.11341  .062522   .493333
{txt}s~l_2008 {c |}  {res}-1.156875      .46143   -2.51   0.012  -2.06126 -.252494   .426667
{txt}road_d~y {c |}  {res} .5799563       .8354    0.69   0.488   -1.0574  2.21732   .189921
{txt}maoist~t {c |}  {res}  .094891      .03387    2.80   0.005   .028509  .161273      5.04
{txt}bys~2006 {c |}  {res}-.0010219      .00165   -0.62   0.536  -.004262  .002218   111.693
{txt}bym~2006 {c |}  {res} .0091396       .0037    2.47   0.013   .001889   .01639   66.2667
{txt}ln_~2001 {c |}  {res} .9319441      .58761    1.59   0.113  -.219742  2.08363    13.894
{txt}{hline 9}{c BT}{hline 68}

{com}. //mfx compute, at(mean, landless_gap= -11.684)
. //mfx compute, at(mean, landless_gap= 169.908)
. //mfx compute, at(mean, no_candidates_2008 = 3)
. //mfx compute, at(mean, no_candidates_2008= 310)
. //mfx compute, at(mean, gap_institutional_credit = -22.199)
. //mfx compute, at(mean, gap_institutional_credit = 46.481)
. mfx compute, at(mean, road_density = 0)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 1.2920315
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.2789752      .12093   -2.31   0.021  -.515991 -.041959   .493333
{txt}s~l_2008 {c |}  {res}-.6142207      .17379   -3.53   0.000  -.954841 -.273601   .426667
{txt}road_d~y {c |}  {res} .3079169      .43521    0.71   0.479  -.545072  1.16091         0
{txt}maoist~t {c |}  {res} .0503806      .01771    2.84   0.004   .015673  .085089      5.04
{txt}bys~2006 {c |}  {res}-.0005425       .0009   -0.61   0.545  -.002299  .001214   111.693
{txt}bym~2006 {c |}  {res} .0048525      .00222    2.18   0.029   .000495   .00921   66.2667
{txt}ln_~2001 {c |}  {res} .4947981       .2103    2.35   0.019   .082624  .906972    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. mfx compute, at(mean, road_density = 2.0578)

{txt}Marginal effects after nbreg
      y  = Predicted number of events (predict)
         = {res} 2.1098789
{txt}{hline 9}{c TT}{hline 68}
variable {c |}{col 17}dy/dx{col 26}Std. Err.{col 40}z{col 45}P>|z|{col 52}[    95% C.I.   ]{col 75}X
{hline 9}{c +}{hline 68}
seat_n~8 {c |}  {res}-.4555646      .47322   -0.96   0.336  -1.38305  .471925   .493333
{txt}s~l_2008 {c |}  {res}-1.003018      .69869   -1.44   0.151  -2.37243  .366397   .426667
{txt}road_d~y {c |}  {res} .5028262     1.07366    0.47   0.640  -1.60151  2.60716    2.0578
{txt}maoist~t {c |}  {res} .0822712      .05706    1.44   0.149  -.029568  .194111      5.04
{txt}bys~2006 {c |}  {res} -.000886      .00148   -0.60   0.548   -.00378  .002008   111.693
{txt}bym~2006 {c |}  {res} .0079241      .00603    1.31   0.189  -.003898  .019746   66.2667
{txt}ln_~2001 {c |}  {res}  .808002      .55388    1.46   0.145  -.277587  1.89359    12.359
{txt}{hline 9}{c BT}{hline 68}

{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\Accepted-Final Articles 2014\Civil Wars\Webdata\CW2014.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 2 Feb 2015, 12:50:04
{txt}{.-}
{smcl}
{txt}{sf}{ul off}